Accelerated Data Science 2.8.6 is released

The following changes were made in ADS 2.8.6:

• Resolved an issue in ads opctl build-image job-local when the build of job-local would get stuck. Updated the Python version to 3.8 in the base environment of the job-local image.
• Fixed a bug that prevented the support of defined tags for Data Science job runs.
• Fixed a bug in the entryscript.sh of ads opctl that attempted to create a temporary folder in the /var/folders directory.
• Added support for defined tags in the Data Flow application and application run.
• Deprecated the old :py:class:`~ads.model.ModelDeploymentProperties and :py:class:`~ads.model.ModelDeployer classes, and their corresponding APIs.
• Enabled the uploading of large size model artifacts for the :py:class:`~ads.model.ModelDeployment class.
• Implemented validation for shape name and shape configuration details in Data Science jobs and Data Flow applications.
• Added the capability to create ADSDataset using the Pandas accessor.
• Made Docker dependency optional for ads opctl run.
• Provided a prebuilt watch command for monitoring Data Science jobs with ads opctl.
• Eliminated the legacy ads.dataflow package from ADS.

For more information, see Data Science and take a look at our Data Science blog.